---
title: Make predictions
description: Make single record or batch predictions in No-Code AI Apps.

---

# Make predictions {: #make-predictions }

There are two ways to make predictions in No-Code AI Apps: [batch predictions](#batch-predictions) or [single record predictions](#single-record-predictions).

!!! note 
    All prediction requests are sent to DataRobot for processing, therefore, applications have the same prediction limits as the main DataRobot platform.

## Batch predictions {: #batch-predictions}

To make multiple prediction requests at once from the **Home** page, click **choose file** or drag the files into the box.

![](images/use-app-7.png)

!!! note
    Anonymous users (i.e., those accessing an application through a sharing link) can only submit batch predictions using a local file (CSV), while signed-in users can submit batch predictions using a local file (XLSX or CSV) or the AI Catalog. When signed-in users submit a batch prediction using a local XLSX file, it is automatically registered in the catalog.

After adding new files, the application processes your predictions and displays them in the **All Rows** widget on the **Home** page. Click on any record to view the prediction results.

![](images/app-all-row.png)

## Single record predictions {: #single-record-predictions}

To make a new prediction:

1. Click **Add new row**, bringing you to the **Create Prediction** page with the **Add New Row** widget, which displays the features available to make a prediction.

    ??? faq "Why aren't some of my features showing up?"
        **Reason 1:** By default, the **Add New Row** widget only displays 10 features.

        To display additional features, click **Show more** at the bottom of the widget. If there are still features missing, you must add them to the widget in **Build** mode. To add features, see the documentation on [managing widget features](app-widgets#manage-widget-features).

        **Reason 2:** No-Code AI Apps only uses "prediction features," meaning features that impact the deployment's predictions.

2. Fill in the feature fields&mdash;at least one field must have a value&mdash; and the [association ID](accuracy-settings#select-an-association-id) if one was added for the deployment. If a field is left blank, the feature field displays _N/A_ on the prediction results page. Alternatively, you can click **Populate averages** to fill in the fields with the average value for each numeric feature and the first alphabetically ordered value of a categorical feature.

    ![](images/use-app-5.png)

    ??? note "Location features for geospatial projects"
        If the dataset contains a location feature, a globe icon appears in the feature field. You can manually enter a feature value in the field, or click the globe icon to view a visual representation of the training data.

        ![](images/use-app-17.png)

        The geometry type of the location feature determines the appearance of the training data on the map and affects which draw tool&mdash;Point, Polygon, or Path&mdash;you can use to highlight your prediction. In the example below, the location feature uses point geometry, so use the **Point** tool to add a new point to the map. With the point selected, click **Save selected location**; the point is then converted to a geojson string to make your prediction.

        ![](images/use-app-18.png)

Click **Add**. After DataRobot completes the request, the prediction results page opens.

To add or remove feature fields, click **Build** and navigate to the **Create Prediction** page.